slide1 n.
Download
Skip this Video
Loading SlideShow in 5 Seconds..
Alan F. Hamlet JISAO/CSES Climate Impacts Group Dept. of Civil and Environmental Engineering PowerPoint Presentation
Download Presentation
Alan F. Hamlet JISAO/CSES Climate Impacts Group Dept. of Civil and Environmental Engineering

Loading in 2 Seconds...

play fullscreen
1 / 80

Alan F. Hamlet JISAO/CSES Climate Impacts Group Dept. of Civil and Environmental Engineering - PowerPoint PPT Presentation


  • 148 Views
  • Uploaded on

Quantifying the Effects of Climate Variability and Change on Hydrologic Extremes in the Pacific Northwest. Alan F. Hamlet JISAO/CSES Climate Impacts Group Dept. of Civil and Environmental Engineering University of Washington. CBCCSP Research Team Lara Whitely Binder Pablo Carrasco

loader
I am the owner, or an agent authorized to act on behalf of the owner, of the copyrighted work described.
capcha
Download Presentation

Alan F. Hamlet JISAO/CSES Climate Impacts Group Dept. of Civil and Environmental Engineering


An Image/Link below is provided (as is) to download presentation

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.


- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -
    Presentation Transcript
    1. Quantifying the Effects of Climate Variability and Change on Hydrologic Extremes in the Pacific Northwest • Alan F. Hamlet • JISAO/CSES Climate Impacts Group • Dept. of Civil and Environmental Engineering • University of Washington

    2. CBCCSP Research Team Lara Whitely Binder Pablo Carrasco Jeff Deems Marketa McGuire Elsner Alan F. Hamlet Carrie Lee Se-Yeun Lee Dennis P. Lettenmaier Jeremy Littell Guillaume Mauger Nate Mantua Ed Miles Kristian Mickelson Philip W. Mote Rob Norheim Erin Rogers Eric Salathé Amy Snover Ingrid Tohver Andy Wood http://www.hydro.washington.edu/2860/products/sites/r7climate/study_report/CBCCSP_chap1_intro_final.pdf

    3. The Myth of Stationarity: 1) Climate Risks are stationary in time. 2) Observed streamflow records are the best estimate of future variability. 3) Systems and operational paradigms that are robust to past variability are robust to future variability.

    4. The Myth of Stationarity Meets the Death of Stationarity Muir Glacier in Alaska Aug, 13, 1941 Aug, 31, 2004 Image Credit: National Snow and Ice Data Center, W. O. Field, B. F. Molnia http://nsidc.org/data/glacier_photo/special_high_res.html

    5. Why a Focus on Hydrologic Extremes? Many human and natural systems are quite robust under “normal” conditions, but have the potential to be profoundly impacted by hydrologic extreme events.

    6. Floods

    7. Drought Evacuated Reservoir During the 2001 PNW Drought

    8. Wildfire

    9. Low Flow and Temperature Impacts to Fish Temperature/ Disease Related Fish Kill in the Klamath River in 2002

    10. Dissolved Gas Management Tailrace below Bonneville Dam

    11. Dam Safety Aftermath of the Johnstown Flood 1889

    12. Dilution Flows for Industrial Pollutants

    13. Stormwater Management

    14. Sediment Transport and Mudslides

    15. Nuts and Bolts: Traditional Methods for Estimating Hydrologic Extremes

    16. Step 1: Select Extreme Event from Each Historical Year Streamflow (cfs) Day of the Water Year (1 = Oct 1)

    17. Step 2: Rank Extreme Events for All Years and Estimate Quantiles 1999 Streamflow (cfs) Probability of Exceedance

    18. Step 3: Fit a Probability Distribution to the Data • Examples of Commonly Used Probability Distributions: • Extreme Value Type 1 (EV 1) • Log Normal (LN) • Log Pearson • Generalized Extreme Value (GEV) • For climate change experiments, GEV is a good choice since the true nature of the future probability distributions is essentially unknown. However it turns out that the choice of distribution is not very critical in terms of the evaluating the sensitivity to warming and/or precipitation change.

    19. Step 4: Estimate Extremes Associated with Return Intervals Site Name Ret. Int. Flow (cfs) SNOMO : 20 68660 SNOMO : 50 81332 SNOMO : 100 91145 Note that any return interval can be estimated. E.g. one could provide an estimate of the “5000 year flood”.

    20. Step 5 (Optional) : Regionalize the Results In order to avoid the inherent “noise” that comes with using imperfect site specific data, a common approach is to “regionalize” the results. The idea is to pool as many sites as possible that have common hydroclimatic features (e.g. sites in western WA), and express the flood statistics as a simple ratio to the mean annual flood (MAF) averaged over many different basins. E.g. Q100 = 2.7 * MAF This approach is used by Ecology in providing estimates of extreme events for the Dam Safety Program, for example.

    21. Low flow analysis is essentially the same except we select the extreme low flow event from each year. 7Q10, for example, extracts the lowest 7-day running mean flow from each historical year, fits a probability distribution to the sequence of extremes, and selects the 90% exceedance value (i.e. a 10% probability of being at or below this extreme value)

    22. Historical Perspectives: Changing Flood Risk in the 20th Century

    23. References: Niemann, PJ, LJ Schick, FM Ralph, M Hughes, GA Wick, 2010: Flooding in Western Washington: The Connection to Atmospheric Rivers, J. of Hydrometeorology, (in review) Hamlet AF, Lettenmaier DP (2007) Effects of 20th century warming and climatevariability on flood risk in the western U.S. Water Resour Res, 43:W06427.doi:10.1029/2006WR005099

    24. Observed Characteristics of Extreme Precipitation Events

    25. Evidence of Changing Flood Statistics

    26. Role of Atmospheric Rivers in Flooding (Nov 7, 2006) Niemann, PJ, LJ Schick, FM Ralph, M Hughes, GA Wick, 2010: Flooding in Western Washington: The Connection to Atmospheric Rivers, J. of Hydrometeorology, (in review)

    27. Role of Atmospheric Rivers in Flooding (Oct 20, 2003) Niemann, PJ, LJ Schick, FM Ralph, M Hughes, GA Wick, 2010: Flooding in Western Washington: The Connection to Atmospheric Rivers, J. of Hydrometeorology, (in review)

    28. Niemann, PJ, LJ Schick, FM Ralph, M Hughes, GA Wick, 2010: Flooding in Western Washington: The Connection to Atmospheric Rivers, J. of Hydrometeorology, (in review)

    29. Modeling Studies of Changing 20th Century Flood Risk in the West

    30. Schematic of VIC Hydrologic Model • Sophisticated, fully distributed, physically based hydrologic model • Widely used globally in climate change applications • 1/16 Degree Resolution (~5km x 6km or ~ 3mi x 4mi) General Model Schematic Snow Model

    31. Evaluating the Hydrologic Model Simulations in the Context of Reproducing Flood Characteristics Ln (X100 / Xmean) OBS Avg WY Date of Flooding OBS Avg WY Date of Flooding VIC Ln (X100 / Xmean) VIC Red = PNW, Blue = CA, Green = Colo, Black = GB

    32. 100-yr Red = VIC Blue = OBS 50-yr X100 GEV flood/mean flood 20-yr 10-yr 5-yr Zp

    33. Regionally Averaged Temperature Trends Over the Western U.S. 1916-2003 Tmax PNW GB Tmin CA CRB

    34. Detrended Temperature Driving Data for Flood Risk Experiments “Pivot 2003” Data Set Temperature Historic temperature trend in each calendar month “Pivot 1915” Data Set 2003 1915

    35. Simulated Changes in the 20-year Flood Associated with 20th Century Warming DJF Avg Temp (C) X20 2003 / X20 1915 DJF Avg Temp (C) X20 2003 / X20 1915 X20 2003 / X20 1915

    36. Schematic of a Cool Climate Flood Precipitation Produces Runoff Precipitation Produces Snow Precipitation Produces Snow Snow Snow Freezing Level Snow Melt

    37. Schematic of a Warm Climate Flood Precipitation Produces Runoff Precipitation Produces Snow Precipitation Produces Snow Snow Snow Snow Melt Freezing Level

    38. Regionally Averaged Cool Season Precipitation Anomalies PRECIP

    39. 20-year Flood for “1973-2003” Compared to “1916-2003” for a Constant Late 20th Century Temperature Regime DJF Avg Temp (C) X20 ’73-’03 / X20 ’16-’03 X20 ’73-’03 / X20 ’16-’03

    40. Summary of Flooding Impacts Rain Dominant Basins: Increases in flooding due to increased precipitation intensity, but no significant change from warming alone. Mixed Rain and Snow Basins Along the Coast: Strong increases due to warming and increased precipitation intensity (both effects increase flood risk) Inland Snowmelt Dominant Basins: Relatively small overall changes because effects of warming (decreased risks) and increased precipitation intensity (increased risks) are typically in the opposite directions.

    41. Effects of ENSO and PDO on Flood Risk

    42. X100 wENSO / X100 2003 X100 nENSO / X100 2003 X100 cENSO / X100 2003 DJF Avg Temp (C) DJF Avg Temp (C) DJF Avg Temp (C) X100 wENSO / X100 2003 X100 nENSO / X100 2003 X100 cENSO / X100 2003

    43. X100 wPDO / X100 2003 X100 nPDO / X100 2003 X100 cPDO / X100 2003 DJF Avg Temp (C) DJF Avg Temp (C) DJF Avg Temp (C) X100 wPDO / X100 2003 X100 nPDO / X100 2003 X100 cPDO / X100 2003

    44. Scenarios of Flood Risk in the 21th Century

    45. 21st Century Climate Impacts for the Pacific Northwest Region Mote, P.W. and E. P. Salathe Jr., 2009: Future climate in the Pacific Northwest

    46. Seasonal Precipitation Changes for the Pacific Northwest http://cses.washington.edu/db/pdf/wacciach1scenarios642.pdf

    47. HumanHealth Infrastructure Water Resources Agriculture/Economics A comprehensive climate change impacts assessment for Washington State Coasts Energy Forest Resources Salmon Adaptation

    48. The Columbia Basin Climate Change Scenarios Project 297 Streamflow Sites This 3-year research project was designed to provide a comprehensive suite of 21st century hydroclimatological scenarios for the Columbia River basin and coastal drainages in OR and WA. Collaborative Partners: • WA State Dept. of Ecology (via HB 2860) • Bonneville Power Administration • Northwest Power and Conservation Council • Oregon Water Resources Department • BC Ministry of the Environment

    49. Columbia Basin Climate Change Scenarios Project 297 Sites • Smaller basins down to • ~500 km2 • Monthly and daily streamflow time series • Assessment of hydrologic extremes • (e.g. Q100 and 7Q10)

    50. Available PNW Scenarios 2020s – mean 2010-2039; 2040s – mean 2030-2059; 2080s – mean 2070-2099